Traditional media systems recommend content in accordance with user preferences recorded in a user profile associated with the user. Traditional systems avoid recommending content inconsistent with preferences in the user profile. For example, a user may have recorded a preference of dislike for content with a particular attribute (e.g. violence) at a certain time in the past. Based on this preference, a media guidance application may not recommend violent movies (‘Silence of the Lambs’) to the user based on this received preference. In some cases, a provider may wish to promote a media asset inconsistent with the profile (e.g., ‘American Psycho’, a violent movie). Selection of that promotion by the user is unlikely because the user is disinterested because of the violent nature of the media asset. The user may pick the promoted media asset only in the unlikely scenario when he feels adventurous. Such systems fail to effectively expose the user to new media as the user will continue viewing content they are most comfortable with and thus the user does not optimally consume content.